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Abstract. Recent global water quality crises point to an urgent need for greater understanding of cyanobacterial harmful algal blooms (cHABs) and their drivers. Nearshore areas of Lake Erie such as Sandusky Bay may become seasonally limited by nitrogen (N) and are characterized by distinct cHAB compositions (i.e., Planktothrix over Microcystis). This study investigated phytoplankton N uptake pathways, determined drivers of N depletion, and characterized the N budget in Sandusky Bay. Nitrate (NO − 3 ) and ammonium (NH + 4 ) uptake, N fixation, and N removal processes were quantified by stable isotopic approaches. Dissimilatory N reduction was a relatively modest N sink, with denitrification, anammox, and N 2 O production accounting for 84, 14, and 2 % of sediment N removal, respectively. Phytoplankton assimilation was the dominant N uptake mechanism, and NO − 3 uptake rates were higher than NH + 4 uptake rates. Riverine N loading was sometimes insufficient to meet assimilatory and dissimilatory demands, but N fixation alleviated this deficit. N fixation made up 23.7-85.4 % of total phytoplankton N acquisition and indirectly supports Planktothrix blooms. However, N fixation rates were surprisingly uncorrelated with NO − 3 or NH + 4 concentrations. Owing to temporal separation in sources and sinks of N to Lake Erie, Sandusky Bay oscillates between a conduit and a filter of downstream N loading to Lake Erie, delivering extensively recycled forms of N during periods of low export. Drowned river mouths such as Sandusky Bay are mediators of downstream N loading, but climate-change-induced increases in precipitation and N loading will likely intensify N export from these systems.

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Phytoplankton blooms are a global water quality issue, and successful management depends on understanding their responses to multiple and interacting drivers, including nutrient loading and climate change. Here, we examine a long-term dataset from Lake 227, a site subject to a fertilization experiment (1969-present) with changing nitrogen:phosphorus (N:P) ratios. We applied a process-oriented model, MyLake, and updated the model structure with nutrient uptake kinetics that incorporated shifting N:P and competition among phytoplankton functional groups. We also tested different temperature and P-loading scenarios to examine the interacting effects of climate change and nutrient loading on phytoplankton blooms. The model successfully reproduced lake physics over 48 yr and the timing, overall magnitude, and shifting community structure (diazotrophs vs. non-diazotrophs) of phytoplankton blooms. Intra-and interannual variability was captured more accurately for the P-only fertilization period than for the high N:P and low N:P fertilization periods, highlighting the difficulty of modeling complex blooms even in well-studied systems. A model scenario was also run which removed climate-driven temperature trends, allowing us to disentangle concurrent drivers of blooms. Results showed that increases in water temperature in the spring led to earlier and larger phytoplankton blooms under climate change than under the effects of nutrient fertilization alone. These findings suggest that successful lake management efforts should incorporate the effects of climate change in addition to nutrient reductions, including intensifying and/or expanding monitoring periods and incorporating climate change into uncertainty estimates around future conditions.

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